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Part of Agent Skills™ by googleadsagent.ai™
The Keyword Research skill delivers a systematic approach to keyword discovery, expansion, and optimization for Google Ads campaigns. Starting from seed keywords, it builds comprehensive keyword universes through multiple expansion vectors: semantic variations, competitor keyword mining, search term report analysis, long-tail discovery, and intent-based grouping. The result is a structured keyword strategy that maximizes relevant coverage while minimizing wasted spend.
Match type selection is a critical component. The skill evaluates each keyword against conversion probability, search volume, competition intensity, and cost-per-click economics to recommend the optimal match type. Broad match keywords are paired with smart bidding strategies, phrase match captures high-intent variations, and exact match locks in proven converters. The skill continuously refines match type assignments based on search term report feedback loops.
Negative keyword management is equally important. The skill mines search term reports for irrelevant queries, builds hierarchical negative keyword lists (account-level, campaign-level, ad-group-level), and maintains shared negative keyword lists across campaigns. Proactive negative keyword discovery prevents budget waste before it occurs by identifying common irrelevant query patterns for each industry vertical.
flowchart TD
A[Seed Keywords] --> B[Expansion Engine]
B --> C[Semantic Expansion]
B --> D[Competitor Mining]
B --> E[Search Term Report]
B --> F[Long-Tail Discovery]
B --> G[Question Queries]
C --> H[Raw Keyword Universe]
D --> H
E --> H
F --> H
G --> H
H --> I[Deduplication & Normalization]
I --> J[Intent Classification]
J --> K[Informational]
J --> L[Commercial]
J --> M[Transactional]
J --> N[Navigational]
L --> O[Match Type Assignment]
M --> O
N --> O
K --> P[Negative Keyword Candidates]
O --> Q[Keyword Grouping Engine]
Q --> R[Themed Ad Groups]
P --> S[Negative Keyword Lists]
S --> T[Account-Level Negatives]
S --> U[Campaign-Level Negatives]
S --> V[Ad Group-Level Negatives]
R --> W[Final Keyword Strategy]
T --> W
U --> W
V --> WKeyword expansion and match type assignment engine:
const MATCH_TYPES = {
BROAD: 'BROAD',
PHRASE: 'PHRASE',
EXACT: 'EXACT'
};
const INTENT_CATEGORIES = ['informational', 'commercial', 'transactional', 'navigational'];
async function expandKeywords(seedKeywords, config) {
const { customerId, industry, maxKeywords = 500 } = config;
const expansionResults = await Promise.all([
semanticExpansion(seedKeywords),
competitorKeywordMining(seedKeywords, industry),
searchTermReportMining(customerId),
longTailDiscovery(seedKeywords),
questionQueryExpansion(seedKeywords)
]);
const rawKeywords = deduplicateAndNormalize(expansionResults.flat());
const classifiedKeywords = rawKeywords.map(kw => ({
...kw,
intent: classifyIntent(kw.text),
suggestedMatchType: assignMatchType(kw)
}));
return classifiedKeywords.slice(0, maxKeywords);
}
function assignMatchType(keyword) {
if (keyword.conversionRate > 0.05 && keyword.volume < 1000) {
return MATCH_TYPES.EXACT;
}
if (keyword.intent === 'transactional' && keyword.wordCount >= 3) {
return MATCH_TYPES.PHRASE;
}
if (keyword.volume > 5000 && keyword.competitorPresence) {
return MATCH_TYPES.BROAD;
}
return MATCH_TYPES.PHRASE;
}
function classifyIntent(keywordText) {
const transactionalSignals = ['buy', 'order', 'purchase', 'price', 'cost', 'cheap', 'deal', 'discount', 'coupon', 'hire', 'book'];
const commercialSignals = ['best', 'top', 'review', 'compare', 'vs', 'alternative', 'recommended'];
const informationalSignals = ['how', 'what', 'why', 'when', 'guide', 'tutorial', 'tips'];
const text = keywordText.toLowerCase();
if (transactionalSignals.some(s => text.includes(s))) return 'transactional';
if (commercialSignals.some(s => text.includes(s))) return 'commercial';
if (informationalSignals.some(s => text.includes(s))) return 'informational';
return 'commercial';
}Negative keyword mining and list management:
async function mineNegativeKeywords(customerId, lookbackDays = 30) {
const searchTerms = await getSearchTermReport(customerId, lookbackDays);
const negatives = searchTerms.filter(term => {
const hasClicks = term.clicks > 0;
const noConversions = term.conversions === 0;
const highSpend = term.costMicros > 5000000;
const lowCTR = term.ctr < 0.01;
const irrelevantIntent = term.classifiedIntent === 'informational';
return hasClicks && noConversions && (highSpend || lowCTR || irrelevantIntent);
});
return categorizeNegatives(negatives);
}
function buildNegativeKeywordLists(negatives) {
return {
accountLevel: negatives.filter(n => n.universallyIrrelevant),
campaignLevel: groupBy(negatives.filter(n => n.campaignSpecific), 'campaignId'),
adGroupLevel: groupBy(negatives.filter(n => n.adGroupSpecific), 'adGroupId'),
sharedLists: buildSharedLists(negatives)
};
}
function groupKeywordsIntoAdGroups(keywords, maxPerGroup = 20) {
const groups = [];
const themes = extractThemes(keywords);
for (const theme of themes) {
const themeKeywords = keywords.filter(kw => kw.theme === theme.id);
if (themeKeywords.length <= maxPerGroup) {
groups.push({ theme: theme.name, keywords: themeKeywords });
} else {
const subGroups = splitBySubTheme(themeKeywords, maxPerGroup);
groups.push(...subGroups);
}
}
return groups;
}The Keyword Research skill serves as the strategic foundation within Buddy™ Agent. When a user connects their account, Buddy™ immediately analyzes existing keyword coverage and identifies expansion opportunities. The skill runs continuously in the background, monitoring search term reports for emerging query patterns and new negative keyword candidates.
Buddy™ presents keyword recommendations through an interactive interface where users can approve, modify, or reject suggestions before they're applied. Approved keywords flow into the appropriate campaigns with match types and bids pre-configured based on predicted performance. Negative keywords are automatically categorized and applied at the correct level.
The skill cross-references with the Competitor Analysis skill to identify keyword gaps where competitors are capturing traffic the account is missing, and feeds into the Ad Copy Generation skill to ensure new keywords have corresponding ad copy.
| Platform | Supported |
|---|---|
| Claude Code | ✅ |
| Cursor | ✅ |
| Codex | ✅ |
| Gemini | ✅ |
keyword research, keyword expansion, negative keywords, match type optimization, broad match, phrase match, exact match, search term mining, keyword grouping, ad group structure, long-tail keywords, keyword intent, keyword strategy, google ads keywords, ppc keywords
© 2026 googleadsagent.ai™ | Agent Skills™ | MIT License
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